Many businesses are already using AI without realizing how widespread it has become.

Examples include:

  • Microsoft Copilot
  • ChatGPT and other LLM tools
  • AI-driven HR screening systems
  • fraud detection models
  • customer service chatbots
  • predictive analytics platforms
  • security monitoring tools

Without a register, organizations face:

⚠️ lack of visibility
⚠️ unmanaged risk
⚠️ unclear accountability
⚠️ compliance exposure
⚠️ shadow AI usage

The AI Act follows a risk-based approach, meaning obligations increase depending on how the system is used.

For example, AI used in:

  • recruitment
  • employee monitoring
  • access to services
  • credit scoring
  • healthcare
  • education

may be classified as high-risk.

These systems require stricter governance and documentation.

Governance: The Register Alone Is Not Enough

An inventory is only the first step.

Organizations must also establish AI governance policies and procedures.

This ensures that AI systems are used responsibly, securely, and compliantly.

Key governance documents should include:

1. AI Acceptable Use Policy

This policy defines:

  • who can use AI tools
  • approved AI platforms
  • prohibited use cases
  • rules for entering sensitive data
  • output review requirements

This is critical for controlling employee use of public AI tools.

2. AI Risk Assessment Procedure

Every new AI system should go through a documented review process.

This should assess:

  • legal risks
  • privacy risks
  • bias and fairness risks
  • cybersecurity risks
  • business impact
  • third-party vendor risks

3. Approval Workflow

Before any AI tool is deployed, it should pass through:

✔ IT
✔ security
✔ legal / compliance
✔ data protection
✔ business leadership

This creates accountability.

4. Human Oversight Procedure

The AI Act strongly emphasizes human oversight, especially for high-risk systems.

Organizations need clear procedures for:

  • who reviews AI outputs
  • when human intervention is required
  • how overrides are documented
  • escalation routes

5. Monitoring and Review Process

AI systems evolve over time.

This means companies need periodic reviews for:

  • model performance
  • drift
  • bias
  • security issues
  • access rights
  • vendor changes

AI governance must be continuous.

Final Thoughts

AI is becoming part of every business function.

Without visibility and governance, that creates significant risk.

Every company should now establish:

✔ an AI systems register
✔ governance ownership
✔ policies and procedures
✔ approval workflows
✔ monitoring controls

The organizations that start now will be far ahead in compliance readiness and responsible AI adoption.

The AI Act is not just regulation.

It is a framework for trustworthy AI governance.